Schizophrenia, marijuana use, and alcohol abuse are just several disorders that are related to accelerated brain aging

Based on one of the biggest brain imaging studies ever done, we can now track common disorders and conducts that prematurely age the brain. Better treatment of these disorders can slow or even halt the process of brain aging. The marijuana abuse finding was especially important, as our culture is starting to see cannabis as an innocuous substance.

The current study used brain SPECT imaging to determine aging trajectories in the brain and which common brain disorders predict unusually accelerated aging. It inspected these functional neuroimaging scans from a large multi-site psychiatric clinic from patients who had many different psychiatric disorders, including bipolar disorder, schizophrenia and attention deficit hyperactivity disorder.

Researchers studied 128 brain regions to predict the chronological age of the patient. Older age predicted from the scan compared to the actual chronological age was interpreted as accelerated aging. The study found that a number of brain disorders and behaviors predicted accelerated aging, especially schizophrenia, which showed an average of 4 years of premature aging, cannabis abuse (2.8 years of accelerated aging), bipolar disorder (1.6 years accelerated aging), ADHD (1.4 years accelerated aging) and alcohol abuse (0.6 years accelerated aging). Interestingly, the researchers did not observe accelerated aging in depression and aging, which they hypothesize may be due to different types of brain patterns for these disorders.

This is one of the first population-based imaging studies, and these large studies are essential to answer how to maintain brain construction and function during aging. The effect of modifiable and non-modifiable factors of brain aging will further guide advice to maintain cognitive function.

This paper represents an important step forward in our understanding of how the brain operates throughout the lifetime. The results designate that we can predict an individual’s age based on patterns of cerebral blood flow. Additionally, groundwork has been laid to further explore how common psychiatric illnesses can influence healthy patterns of cerebral blood flow.